Energy-dispersive radiation spectrometry systems, such as, without limitation, X-ray spectrometry systems or gamma-ray spectrometry systems, are used for detecting, measuring and analyzing radiation emissions, such as X-ray emissions or gamma-ray emissions, from, for example, a scanning electron microscope (SEM). A typical energy-dispersive radiation spectrometry system includes the following four main components: (1) a detector, (2) a pre-amplifier, (3) a pulse processor, and (4) a computer-based analyzer. For convenience only, and not for purposes of limitation, the following description will relate to X-ray spectrometry systems and photons in the form of X-rays (as compared to, for example, photons in the form of gamma-rays that are detected in a gamma-ray spectrometry system).
The detector, which usually takes the form of a semiconductor sensor of some type, converts an incoming X-ray into a very small current pulse, typically on the order of tens of thousands of electrons, with a duration of about tens to a few hundreds of nanoseconds. The magnitude of each of the current pulses is proportional to the energy of the X-ray.
The pre-amplifier amplifies the current pulse output by the detector and typically converts it into a voltage signal in the range of tenths of millivolts up to a few hundreds of millivolts. There are two main types of preamplifiers: “tail pulse” or RC-coupled preamplifiers, and pulsed-reset preamplifiers. In a pulsed-reset type of preamplifier, the charge generated in the sensor is integrated in a feedback capacitor such that the resulting voltage increases in steps of varying heights and intervals, until it reaches an upper limit. When that limit is reached, a “reset” pulse is applied which drains the accumulated charge from the feedback capacitor, restoring the preamplifier to near its minimum output voltage in a short time, typically a few microseconds. Then, charge due to the interaction of X-rays with the detector accumulates on the feedback capacitor again, and the cycle repeats. In contrast, tail-pulse preamplifiers act as high-pass filters on the voltage step signal output by the detector, with an exponential return to baseline whose time constant is long compared to the charge integration time in a feedback capacitor of the preamplifier. The subject matter described elsewhere herein applies to pulsed-reset preamplifiers.
The pulse processor receives the pre-amplifier signal and generates a numeric representation of the X-ray's energy through an integration process. In older energy-dispersive radiation spectrometry systems, the pulse processor included two separate components, namely a “shaping amplifier” and an analog to digital converter. Modern energy-dispersive radiation spectrometry systems, on the other hand, typically combine these functions, with the newest designs digitizing the preamplifier signal directly and carrying out all pulse detection and filtering functions using digital signal processing. The subject matter described elsewhere herein applies to all-digital pulse processing.
The computer-based analyzer accumulates the X-ray energies output by the pulse processor into a spectrum or plot of the number of X-rays detected against their energies. The spectrum is divided into a somewhat arbitrary number of small ranges called “channels” or “bins.” In older systems, a hardware component called a multi-channel analyzer (MCA) did the accumulation of X-rays into spectrum channels and a computer read out the summed result. In modern systems, the MCA function is handled in software, either by the computer or even within the pulse processor.
The job of the pulse processor is made more complex by several factors. For example, electronic noise is superimposed on the underlying signal received from the preamplifier. For X-rays that are near the lowest detectable energy level, the preamplifier output step height may be significantly smaller than the peak-to-peak excursions of the electronic noise. In such as case, the X-ray can only be detected by filtering the signal for a relatively long period of time before and after the step, to average away the contribution of the noise.
Second, the steps in the preamplifier output are not instantaneous. In the absence of noise, the signal would be a sigmoidal (S-shaped) curve. This is due to bandwidth limitations, device capacitance, and the time required for all the electrons generated by an X-ray to reach the anode of the sensor. These electrons can be visualized as a small cluster or cloud, which moves through the sensor material toward the anode under the influence of the bias voltage field within the semiconductor sensor.
In addition to the electrons generated by X-rays, there is also a slow continuous flow of electrons to the feedback capacitor of the preamplifier due to leakage. This leakage current appears as a slight positive slope in the preamplifier output even in the absence of X-rays. The amount of leakage current is a strong function of temperature in semiconductor detectors; in silicon devices, leakage approximately doubles for each 7 degree C. increase in temperature. The newest generation of commercial silicon sensors, referred to as “Silicon Drift Detectors” (SDDs), operate at much higher temperatures than traditional so called Lithium-Drifted Silicon (Si(Li)) which must be cooled to liquid nitrogen temperature for proper operation. Thus, leakage currents are much higher when SDDs are employed and the background slope in the preamplifier output is correspondingly higher as well.
The most common type of digital filter used in digital pulse processing is the so-called triangle or trapezoidal filter, which is illustrated in FIGS. 2A-2C. A triangle or trapezoidal filter simply takes an average of the preamplifier signal during a short period of time before a step edge and afterwards, possibly separated by a small gap of zero weight, and subtracts them as shown in FIG. 2A. This type of filtering is well-known in the art, and is popular because it is very easy to compute. Only four arithmetic operations are required per sample of the digitized preamplifier waveform for a continuous convolution of the filter with the digitized waveform. The response of such a convolution, as shown in the middle portion of FIG. 2C, is a triangle (possibly with a flat top if there is a gap in the filter), hence the common name for this type of filtering.
If the background slope of the signal is not zero, as shown by the dotted line in FIG. 2B, a triangular or trapezoidal filter convolved with it will have a constant response equal to the shaded area of FIG. 2B. When a step edge is superimposed, the resulting maximum response of the filter is increased by a constant amount as shown in the bottom portion of FIG. 2C. This has been known in the art for more than 30 years, and was described in 1975 by U.S. Pat. No. 3,872,287 to Koeman. If the background slope is known, the measured energy of the X-ray can be corrected for the effects of the background slope by subtracting the known response of a digital filter to the slope.
The classical method of determining the slope, as described by the '287 patent and also used in some commercial analog pulse processors, is to trigger an energy measurement artificially in the absence of an X-ray. The average response of a large number of such artificial triggerings will be the offset required to correct the energy of a response to a real X-ray. But as the '287 patent notes, this makes the assumption that the background slope is constant.
Leakage current is indeed expected to be constant if (as noted above) the sensor's temperature is held constant, but there are other potential sources of background slope in the signal which may not be constant over time. The aftereffects of a reset may induce a slow exponential change in the background slope, depending on the design of the preamplifier. Various kinds of low-frequency noise coupled into the preamplifier output, most commonly at power-line frequencies, can also cause the local slope to vary with time. The phenomenon known in the art as “microphonics” describes the coupling of acoustic signals from the environment into the preamplifier signal, as physical components of the detector assembly act as capacitive microphones. The effect of a time-varying background slope is to cause the entire spectrum, including the artificially-triggered peak, to both move up and down in energy. As a result, averaged over time, the center of the artificially-triggered peak may still represent the average offset, but the peaks will be significantly broadened by the instability of the peak positions.
U.S. Pat. No. 5,349,193 to Mott discloses a method for estimating the local slope in the neighborhood of a step edge. The '193 patent also shows the effects of slope in FIG. 6g thereof, and of time-varying slope in FIG. 6h thereof. Looking at FIG. 4 of the '193 patent, block 48 and the accompanying text describe a triangle filter used to detect edges of all energies. Block 48 is detailed in FIG. 6a, where the three arithmetic logic units (ALUs) 202, 204, and 206 make up the triangle filter, and FIFO 210 with accumulator 208 accumulate a running sum of 2SC successive outputs of the peak-detecting filter. The filter output is also tested against an energy threshold in comparator 214, and the accumulation in FIFO 210 is blocked if the output is above threshold. In this way, only samples from the background slope are accumulated in the FIFO. The average of the slope (simply computed by bit-shifting the sum down SC bits in block 220) is used to correct the data stream before energy-measurement filters in block 52 are applied. This eliminates the need for a separate correction factor for each of the many measurement filters stored in the coefficient tables in blocks 58 and 60.
While the method described in the '193 patent is effective, there is room for improvement in the area of slope correction in digital pulse processing.